* Select a company that you work for or with which you are familiar with and describe its operations strategy and how it relates to “winning” customers.

I work for a GridX, a data analytics company that uses utility customer smart meter data to support utilities and customers in making clean energy technology decisions. The company’s strategy is to sell its analytics solutions to utilities, performing calculations for utilities on how much it costs for a customer to adopt a clean energy technology such as an electric vehicle, solar, heat pumps, or a new rate. These calculations support utility rate and program design, and provides greater customer satisfaction as it enables the utility to become the customer energy advisor on their clean energy choices.

The company’s process includes utilizing interval data and billing insights. The company first correctly recreates the utility’s billing logic to recreate customer bills and run analyses on. By ensuring its bills match those in the utility’s billing system, the company can ensure that its calculations and consequent analyses are accurate and reliable. Upon running its analyses the company then provides the cost insights to the utility via its APIs.

* Describe specific activities used by the company that support the strategy
Specific activities include that the company has the the right labor, the right technology, market research to ensure it understands utility and consumer needs and demands (Jacobs & Chase, 2021). This includes ensuring that the company employed skilled product developers, designers, marketers, salespeople to develop the products, market it, sell it, and deliver it.

* Then, explain how using a QFD approach might help in the operations process and how it might be limited in aiding ?
QFD stands for Quality Function Deployment, which is an approach consisting of understand customer needs and using this understanding to produce products to meet those needs. Our company has recently strongly relied on QFD, since its analytics around its rate design product were not in high demand by prospective client utilities. Instead, these prospects did have an interest in meeting growing consumer interest in electric vehicles (EV) and solar, and these prospects had developed programs to support electric vehicle and solar adoption. But both utilities and consumers struggled to accurately identify how much solar adoption would save them on their bill (third party solar estimates were often inaccurate) and EV ownership costs and gas savings tough to estimate. My company consequently utilized its analytics solutions to build out a product that can calculate down to dollars and cents how much a certain size of solar adoption on a customer’s roof will save on their bill, and what the ownership costs are of different EV models under certain charging scenarios. The limiting factor for the company is that building out these products is very expensive, so they will need to sign several utility clients for cost recovery and to meet their margins.

References:
Jacobs, F. R., & Chase, R. (2021). Operations and supply chain management (16th ed.) McGraw-Hill

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